C.07 Predicting individualized risk of recurrence: development and validation of a DNA-methylation based nomogram in meningioma. (June 2019)

• Record Type: Journal Article
• Authors: Nassiri, F; Mamatjan, Y; Suppiah, S; Badhiwala, J; Mansouri, S; Karimi, S; Saarela, O; Poisson, L; Ng, H; Noushmehr, H; Harter, P; Baumgarten, P; Weller, M; Preusser, M; Mende, C; Sahm, F; von Deimling, A; Aldape, K; Zadeh, G
• Is Part Of: Canadian journal of neurological sciences. Volume 46(2019)Supplement 1
• Page Start: S13
• Page End: S13
• Publication Date: 2019-06
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Electronic journals; 616.8
• DOI: 10.1017/cjn.2019.102
• Languages: English
• ISSNs: 0317-1671

Abstract

Abstract : Background: Challenges in predicting risk of recurrence for individual patients with meningioma limits appropriate selection of patients who may benefit from adjuvant radiation therapy to delay recurrence. Here, we aimed to develop and validate a combined clinicomolecular predictor of early recurrence for individual patients with meningiomas. Methods: A methylation-based predictor of 5-year recurrence-free-survival (RFS) was developed using DNA-methylation profiles from a training cohort of 228 patients. Model performance was compared to a standard-of-care histological-based model using three independent cohorts (N=54 ;N=140; N=64 patients). Subsequently, a nomogram that integrated the methylome-based predictor with prognostic clinical factors was developed and validated. Results: The methylome-based predictor of 5-year RFS performed favorably compared to a grade-based predictor when tested using the three validation cohorts (ΔAUC=0. 10, 95%CI 0. 03 – 0. 018) and was independently associated with RFS on multivariable Cox regression analysis (HR=3. 6, 95%CI 1. 8–7. 2, P<0.001). A nomogram combining the methylome-predictor with clinical factors demonstrated greater discrimination for recurrence than a nomogram using clinical factors alone (ΔAUC=0. 25, 95%CI 0. 22–0. 27) and resulted in two risk groups with distinct recurrence patterns (HR=7.7, 95%CI 5.3–11.1, P<0.001) and clinical implications. Conclusions: Our validated models provide important novel prognostic information that could be used to individualize decisions regarding post-operative therapeutic interventions in meningioma.